What happens when a biotech company disappears? We think that the Web remembers everything. Do a search on Wikipedia for Immunex and you get Amgen, with little mention of Immunex at all. The results of over 500 publications and several thousand employees over 20 years are pretty much invisible on the largest collection of facts on the Internet.
One of the most successful stories in Seattle history and it is mostly gone from view. Ten years ago, Amgen announced it was buying Immunex. Xconomy will be commemorating this historic event in December.
Immunex may be gone from the Web but the lessons it taught still have impacts today. Before Immunex completely disappears from view, I wanted to discuss Five Lessons Immunex Taught Me.
• Get to decision points rapidly.
• Live in the gray.
• Size matters.
• Leverage insurrection.
• Vet in the open. And then vet again.
I was a researcher at Immunex for 16 years as it grew from a small community where everyone knew each other to a large, global undertaking with people spread out in multiple locations. While some of these lessons may be part of any good MBA program, there is nothing like dealing with the day-to-day reality to drive the lessons home.
I’ve used these lessons over the 10 years since leaving Immunex – as a Vice President in charge of research at a biotech startup, as a founder of my own organizations, as well as in collaborations with other organizations such as the Sustainable Path Foundation, the WBBA, Global Health Nexus and the Washington Global Health Alliance.
Caveat lector: These are my recollections about events – some of which are over 25 years old—so forgive me if I do not get the events exactly right. After all, these are the lessons Immunex taught me. Others may have learned something different.
1) Get to decision points rapidly. Immunex always worked towards a decision point, an action that would permit us to either kill the project, move forward or change direction. Simply delaying a decision was almost never a consideration.
Shortly after joining Immunex, I was a member of a presentation we gave to one of our collaborators – a company with lots of proprietary chemicals looking to find pharmacologically important ones. Steve Gillis was there along with several other Immunex scientists.
In contrast to the Immunex crew, the people we met seemed more interested in finding reasons to delay a decision for six months or so than in what we had to present. They kept nitpicking rather than moving forward. Any excuse to delay a decision was good enough.
For example, we produced a standard operating procedure for performing a biological assay we had developed to use with their chemicals. It described how to grow the particular cells at several specific temperatures such as 35°C, 37°C and 42°C.
The response from our collaborators? “What about 40°C or 39°C? Or 22°C? We want those in the SOP also. The entire thing needs to be redone to include these.”
Gillis exemplified the Immunex response to this – he simply told them not to run the procedure at those other temperatures. Decision made and we just moved on.
The large company seemed to be afraid to accept our protocol at all, perhaps because they might make a wrong choice. Being wrong was a greater transgression than delaying a decision.
Saying “yes” could be a mistake and so could saying “no.” Delay meant “maybe.” Who could make a mistake with “maybe?”
But delay itself is a decision and usually a poor one in a rapidly moving field, making it very hard to adapt as circumstances change.
That may be why our collaborator never became a big leader in the biotechnology arena. We created billion dollar therapies.
Get to those decision points as efficiently and as effectively as possible, then actually make a decision. This is critical for an innovative company.
Move forward, kill it or change directions. Delay actually can be the same as moving backwards.
2) Live in the gray. While seemingly contradicting the previous point, this actually follows from a key aspect of decision points – the need for as complete a set of data as possible.
Good data is critical for making a decision. Incomplete data can destroy any decision.
Like the Fog of War, the gray of the Fog of Science that often surrounds biomedical research can punish decisions made without proper supporting data. Do we have enough data to let us move forward, kill it or change directions? If not, can getting more
